风电机组确定性机会更换维修策略的研究

在预防性维修基础上引入机会维修的概念,提出采用确定性机会维修策略来实施风电机组的优化维修。在假设风电机组各部件的故障率服从两参数威布尔分布的基础上,对风电机组关键部件的预防维修可靠度和机会维修可靠度进行优化,最小风电机组系统的维修费用。该维修策略是对预防性维修部件与可靠度落入机会维修区间的其他部件实施共同维修,将风电机组关键部件的维修有机结合起来,实现分摊高额的固定维修成本。通过仿真分析,确定性机会维修策略比预防性维修策略节省维修成本,证实确定性机会维修的科学性。     

排队论在风电场最优成组维修决策中的应用

针对风电场高昂的维修准备成本,将单台风电机组(wind turbine,WT)作为整体,风电场视为一个由多设备组成的并联系统,研究风电场的最优成组维修策略。根据排队论分析风电场中WT发生停机性故障的规律,描述对应的维修排队模型,在此基础上,通过固定故障率给出计算单台WT发生停机性故障后等待被维修的平均时间。最后,与传统维修方式对比,以节省总维修成本最大为目标建立最优成组维修模型。数值实验和灵敏度分析验证该模型的正确性和有效性,算例分析结果表明,该成组维修策略能有效降低风电场整体维修成本,实现风电场整体经济效益最优。     

基于风电场机组大部件运行状态的年度检修策略

风电场机组年度检修是保证所有风电机组正常运行的重要手段,合理的检修方案可以降低风电场运行维护成本。为确定风电场的最优年度检修方案,文章提出了一种基于大部件运行状态的风电场年度检修策略。首先,综合考虑大部件的工作役龄、维修历史及当前运行状态,以威布尔比例强度模型计算部件的故障概率;然后,定义检修改善因子,描述年度检修对部件故障概率的降低程度,建立考虑故障停机时间、故障维修费用及检修成本的年度检修策略优化模型;最后,通过算例分析验证该策略的正确性及有效性。     

考虑不完全维修的风电机组预防性机会维修策略

针对风电机组维修方式单一、成本昂贵的问题,提出考虑不完全维修的风电机组预防性机会维修策略。首先采用威布尔分布对风电机组可靠度进行建模,根据预防维修可靠度和机会维修可靠度确定不完全维修可靠度,对处于机会维修区间内的关键部件采取不完全维修和机会更换两种维修方式;采用役龄递减因子和故障率递增因子对不完全维修方式进行建模,进而确定机组的维修计划;然后建立风电机组的维修成本模型,以成本最低为目标,通过三次样条内插法对不完全维修可靠度进行优化;最后结合具体风电机组维修案例进行仿真。结果表明,该策略可以提高部件维修协调性,降低维修成本,从而验证了所提策略的有效性。     

风电机组大部件的备品备件区域库存优化控制策略

风电机组大部件的备品备件是保障风电机组运行的重要物资,合理的备件库存可减少风电场的停机损失。针对风电机组大部件的备品备件库存控制问题,提出了基于(s,Q)策略的区域库存优化控制策略。首先,以威布尔分布函数描述风机大部件的故障概率密度。其次,考虑风电机组设计寿命及备件短缺停机时间,通过概率模型推导了区域库存策略下的风机大部件备件成本和平均可用率公式。然后,以备件成本最小为优化目标,建立库存优化控制模型,并分析了大部件的各主要参数对最优库存控制参数的影响。最后,通过算例分析验证了该策略的有效性。     

考虑不完全维修的风电机组齿轮箱维修策略优化

齿轮箱是风电机组的重要部件,在实际运维中,由于齿轮箱故障维修费用高昂,导致风力发电的整体收益偏低。由此,本文提出了一种针对齿轮箱循环利用的维修策略,引入不完全维修因子,建立动态的不完全预防性维修模型,以单位时间内的运行收益率最大为优化目标,确定风电机组关键部件从全新到抛弃阶段最佳的维修次数和预防性维修间隔。通过对一个算例进行仿真,结果表明,该策略可提高风电机组的单位运行收益,从而验证了该策略的有效性。     

基于多状态空间划分的风电机组非完美维修决策

对风电机组的合理维护维修是减少风电场运维成本的重要方式。同一风电场的多台风力发电机构成了一个典型的多部件系统,各风力发电机的运行性能共同决定了系统整体的运行效率和维修需求。同时,对各风力发电机的维修效果也将影响到系统后续的可利用率和维修决策。该文以同一风电场中多台风力发电机的主轴组成的同型多部件系统为对象,在考虑非完美维修的条件下制定基于周期检测的视情机会维修策略;构建考虑非完美维修的多状态退化空间划分模型,以定义系统状态与维修需求的表示及关系,并归纳推导系统维修需求概率的计算模型和非完美维修干预下的系统退化及维修恢复过程中的状态转移概率;在此基础上,建立系统平均费用率解析模型,以确定最优的检测周期和维修阈值。通过某风电场的主轴实际运行数据进行数值实验,验证策略和模型的正确性和有效性,并对参数进行灵敏度分析以说明模型的适用性。结果表明该策略能有效减少风电场的运维成本。     

考虑时间窗约束的海上风电机组运维方案优化

降低运维成本是保障海上风电经济效益的关键,运维方案优化对降低海上风电机组运维成本和提高发电量起着双重作用。根据风电机组零部件的可靠度模型,计算出每台风电机组最佳维修时机对应的时间窗,考虑提前维修和故障后维修的经济损失,建立包含时间窗约束的海上风电机组运维方案优化模型,然后设计基于参数优化的改进遗传算法计算出最优运维方案。最后采用某海上风电场内风电机组运维案例验证模型和算法,结果表明考虑时间窗约束的运维方案可大幅度提高海上风电的经济效益,改进遗传算法比传统遗传算法具有更强的寻优能力。     

考虑故障相关性的风电机组维修策略

由于一般的风电机组可靠性建模忽略了各子系统间的故障相关性,必然造成可靠性评估的误差。针对这一问题,文章提出了一种考虑故障相关性的风电机组维修策略。首先,运用全概率公式和故障有向图理论,推演出子系统的综合可靠度模型,再将综合可靠度模型应用到风电机组的维修策略中。然后,建立了考虑故障相关性的风电机组状态机会维修模型和定期维修模型,状态机会维修分别采用故障后大修和小修的方法来求解状态维修阈值函数和机会维修阈值函数,定期维修以考虑降低维修费用确定定期维修周期。最后,通过实例仿真验证了考虑故障相关的风电机组维略策略在节约维修成本方面的有效性。     

并网风电机组寿命分布拟合与维修方案评价

风电机组的寿命分布是制定维修策略和优化机组运行的重要依据,研究其寿命分布需要大量的完整寿命数据,然而我国风电机组投入运行的时间短,缺少完整寿命数据。文章首先提出了一种基于部件寿命信息的机组可靠寿命分布拟合方法,该方法根据部件运行寿命信息和机组系统可靠性框图,模拟产生机组的可靠寿命;然后利用灰色关联度定量地选择机组寿命分布拟合函数,对机组的可靠寿命进行分析;最后利用机组可靠寿命分布,提出了基于机组可靠度测度维修方案的量化分析模型。研究结果表明,风电机组寿命分布可用威布尔分布拟合;文章所提出的可靠度测度分析模型能够有效地评价机组维修方案的优劣。     

Optimal selection of time windows for preventive maintenance of offshore wind farms subject to wake losses

The maintenance of wind farms is one of the major factors affecting their profitability. During preventive maintenance, the shutdown of wind turbines causes downtime energy losses. The selection of when and which turbines to maintain can significantly impact the overall downtime energy loss. This paper leverages a wind farm power generation model to calculate downtime energy losses during preventive maintenance for an offshore wind farm. Wake effects are considered to accurately evaluate power output under specific wind conditions. In addition to wind speed and direction, the influence of wake effects is an important factor in selecting time windows for maintenance. To minimize the overall downtime energy loss of an offshore wind farm caused by preventive maintenance, a mixed-integer nonlinear optimization problem is formulated and solved by the genetic algorithm, which can select the optimal maintenance time windows of each turbine. Weather conditions are imposed as constraints to ensure the safety of maintenance personnel and transportation. Using the climatic data of Cape Cod, Massachusetts, the schedule of preventive maintenance is optimized for a simulated utility-scale offshore wind farm. The optimized schedule not only reduces the annual downtime energy loss by selecting the maintenance dates when wind speed is low but also decreases the overall influence of wake effects within the farm. The portion of downtime energy loss reduced due to consideration of wake effects each year is up to approximately 0.2% of the annual wind farm energy generation across the case studies—with other stated opportunities for further profitability improvements.     

Condition based maintenance optimization for wind power generation systems under continuous monitoring

By utilizing condition monitoring information collected from wind turbine components, condition based maintenance (CBM) strategy can be used to reduce the operation and maintenance costs of wind power generation systems. The existing CBM methods for wind power generation systems deal with wind turbine components separately, that is, maintenance decisions are made on individual components, rather than the whole system. However, a wind farm generally consists of multiple wind turbines, and each wind turbine has multiple components including main bearing, gearbox, generator, etc. There are economic dependencies among wind turbines and their components. That is, once a maintenance team is sent to the wind farm, it may be more economical to take the opportunity to maintain multiple turbines, and when a turbine is stopped for maintenance, it may be more cost-effective to simultaneously replace multiple components which show relatively high risks. In this paper, we develop an optimal CBM solution to the above-mentioned issues. The proposed maintenance policy is defined by two failure probability threshold values at the wind turbine level. Based on the condition monitoring and prognostics information, the failure probability values at the component and the turbine levels can be calculated, and the optimal CBM decisions can be made accordingly. A simulation method is developed to evaluate the cost of the CBM policy. A numerical example is provided to illustrate the proposed CBM approach. A comparative study based on commonly used constant-interval maintenance policy demonstrates the advantage of the proposed CBM approach in reducing the maintenance cost.     

An engineering condition indicator for condition monitoring of wind turbine bearings

Condition monitoring (CM) of wind turbine becomes significantly important part of wind farms in order to cut down operation and maintenance costs. The large amount of CM system vibration data collected from wind turbines are posing challenges to operators in signal processing. It is crucial to design sensitive and reliable condition indicator (CI) in wind turbine CM system. Bearing plays an important role in wind turbine because of its high impact on downtime and component replacement. CIs for wind turbine bearing monitoring are reviewed in the paper, and the advantages and disadvantages of these indicators are discussed in detail. A new engineering CI (ECI), which combined the energy and kurtosis representation of the vibration signal, is proposed to meet the requirement of easy applicability and early detection in wind turbine bearing monitoring. The quantitative threshold setting method of the ECI is provided for wind turbine CM practice. The bearing run‐to‐failure experiment data analysis demonstrates that ECI can evaluate the overall condition and is sensitive to incipient fault of bearing. The effectiveness in engineering of ECI is validated though a certain amount of real‐world wind turbine generator and gearbox bearing vibration data.     

Minimizing maintenance cost for offshore wind turbines following multi-level opportunistic preventive strategy

Cost of energy generated from offshore wind is impacted by maintenance cost to a great extent. Cost of maintenance depends primarily on the strategy for performing maintenance. In this paper a maintenance cost model for offshore wind turbine components following multilevel opportunistic preventive maintenance strategy is formulated. In this strategy, opportunity for performing preventive actions on components is taken while a failed component is replaced. Two kinds of preventive actions are considered, preventive replacement and preventive maintenance. In the former, components that undergo that action become as good as new (i.e., the replaced components, are not just as good as new, but are actually new), but in the latter, ages of components are reduced to some degree depending on the level of maintenance action. Total cost associated with maintenance depends on the setting of age groups that determine which component should be preventively maintained and to what degree. Through optimum selection of the number of age groups, cost of maintenance can be minimized. A model is formulated where total maintenance cost is expressed as a function of number of age groups for components. A numerical study is used to illustrate the model. The results show that total cost of maintenance is significantly impacted by number of age groups and age thresholds set for components.     

Combining economic and fluid dynamic models to determine the optimal spacing in very large wind farms

Wind turbine spacing is an important design parameter for wind farms. Placing turbines too close together reduces their power extraction because of wake effects and increases maintenance costs because of unsteady loading. Conversely, placing them further apart increases land and cabling costs, as well as electrical resistance losses. The asymptotic limit of very large wind farms in which the flow conditions can be considered ‘fully developed’ provides a useful framework for studying general trends in optimal layouts as a function of dimensionless cost parameters. Earlier analytical work by Meyers and Meneveau (Wind Energy 15, 305–317 (2012)) revealed that in the limit of very large wind farms, the optimal turbine spacing accounting for the turbine and land costs is significantly larger than the value found in typical existing wind farms. Here, we generalize the analysis to include effects of cable and maintenance costs upon optimal wind turbine spacing in very large wind farms under various economic criteria. For marginally profitable wind farms, minimum cost and maximum profit turbine spacings coincide. Assuming linear‐based and area‐based costs that are representative of either offshore or onshore sites we obtain for very large wind farms spacings that tend to be appreciably greater than occurring in actual farms confirming earlier results but now including cabling costs. However, we show later that if wind farms are highly profitable then optimization of the profit per unit area leads to tighter optimal spacings than would be implied by cost minimization. In addition, we investigate the influence of the type of wind farm layout. © 2016 The Authors Wind Energy Published by John Wiley & Sons Ltd     

基于风电机组可靠性的风电场平准化成本模型研究

考虑综合风电场总体运行成本、风电机组可靠性及风电场发电量等多个维度,从风电场全生命周期视角出发,建立基于风电机组可靠性的风电场平准化成本模型,并通过算例分析得出,提升风电机组可靠性可降低风电机组的故障维护成本,提高风电场运行小时数,进而降低风电场平准化成本。在此基础上测算当前阶段风电实现平价上网需达到的利用小时数,最后给出促进风电发展的合理化建议。     

Power generation efficiency analysis of offshore wind farms connected to a SLPC (single large power converter) operated with variable frequencies considering wake effects

This paper deals with the power generation efficiency analysis of a proposed offshore wind farm topology, consisting of a SLPC (single large power converter) that simultaneously controls a group of generators. This common converter can operate at a VF (variable frequency) or at a CF (constant frequency). The results are compared with the conventional onshore wind farm scheme, where individual power converters are connected to each turbine, guaranteeing maximum power generation for the entire wind farm. A methodology to analyze different wind speed and direction scenarios, and to compute the optimal electrical frequency for each one, is presented and applied to different case studies depending on the wind farm size. In order to obtain more realistic values of wind speeds, the wake effect amongst wind turbines is considered. A wake model considering single, partial and multiple wakes inside a wind farm and taking into account different wind directions, is presented. Both wind farm topologies are analyzed by means of simulations, taking into account both wind speed variability in wind farms and the number of wind turbines. The possible resulting benefits of simplifying the MPCs (multiple power converters) of each turbine, namely saving costs, reducing losses and maintenance and increasing the reliability of the system, are analyzed, focusing on the total power extraction. The SLPC-VF scheme is also compared with a CF scheme SLPC-CF, and it is shown that a significant power increase of more than 33% can be obtained with SLPC-VF.     

A framework for data integration of offshore wind farms

Operation and maintenance play an important role in maximizing the yield and minimizing the downtime of wind turbines, especially offshore wind farms where access can be difficult due to harsh weather conditions for long periods. It contributes up to 25–30% to the cost of energy generation. Improved operation and maintenance (O&M) practices are likely to reduce the cost of wind energy and increase safety. In order to optimize the O&M, the importance of data exchange and knowledge sharing within the offshore wind industry must be realized. With more data available, it is possible to make better decisions, and thereby improve the recovery rates and reduce the operational costs. This article describes the development of a framework for data integration to optimize the remote operations of offshore wind farms.     

Maximum generation power evaluation of variable frequency offshore wind farms when connected to a single power converter

The paper deals with the evaluation of power generated by variable and constant frequency offshore wind farms connected to a single large power converter. A methodology to analyze different wind speed scenarios and system electrical frequencies is presented and applied to a case study, where it is shown that he variable frequency wind farm concept (VF) with a single power converter obtains 92% of the total available power, obtained with individual power converters in each wind turbine (PC). The PC scheme needs multiple power converters implying drawbacks in terms of cost, maintenance and reliability. The VF scheme is also compared to a constant frequency scheme CF, and it is shown that a significant power increase of more than 20% can be obtained with VF. The case study considers a wind farm composed of four wind turbines based on synchronous generators.